class_docstr: An `EventMultiplexer` manages access to multiple `EventAccumulator`s.
  
  Each `EventAccumulator` is associated with a `run`, which is a self-contained
  TensorFlow execution. The `EventMultiplexer` provides methods for extracting
  information about events from multiple `run`s.
  
  Example usage for loading specific runs from files:
  
  ```python
  x = EventMultiplexer({'run1': 'path/to/run1', 'run2': 'path/to/run2'})
  x.Reload()
  ```
  
  Example usage for loading a directory where each subdirectory is a run
  
  ```python
  (eg:) /parent/directory/path/
        /parent/directory/path/run1/
        /parent/directory/path/run1/events.out.tfevents.1001
        /parent/directory/path/run1/events.out.tfevents.1002
  
        /parent/directory/path/run2/
        /parent/directory/path/run2/events.out.tfevents.9232
  
        /parent/directory/path/run3/
        /parent/directory/path/run3/events.out.tfevents.9232
  x = EventMultiplexer().AddRunsFromDirectory('/parent/directory/path')
  (which is equivalent to:)
  x = EventMultiplexer({'run1': '/parent/directory/path/run1', 'run2':...}
  ```
  
  If you would like to watch `/parent/directory/path`, wait for it to be created
    (if necessary) and then periodically pick up new runs, use
    `AutoloadingMultiplexer`
  @@Tensors
docstr: Return the contents for a specific plugin asset from a run.
  
  Args:
    run: The string name of the run.
    plugin_name: The string name of a plugin.
    asset_name: The string name of an asset.
  
  Returns:
    The string contents of the plugin asset.
  
  Raises:
    KeyError: If the asset is not available.
docstr_tok: ["Return","the","contents","for","a","specific","plugin","asset","from","a","run",".","Args",":","run",":","The","string","name","of","the","run",".","plugin_name",":","The","string","name","of","a","plugin",".","asset_name",":","The","string","name","of","an","asset",".","Returns",":","The","string","contents","of","the","plugin","asset",".","Raises",":","KeyError",":","If","the","asset","is","not","available","."]
code: def RetrievePluginAsset(self, run, plugin_name, asset_name):
      """Return the contents for a specific plugin asset from a run.
  
      Args:
        run: The string name of the run.
        plugin_name: The string name of a plugin.
        asset_name: The string name of an asset.
  
      Returns:
        The string contents of the plugin asset.
  
      Raises:
        KeyError: If the asset is not available.
      """
      accumulator = self.GetAccumulator(run)
      return accumulator.RetrievePluginAsset(plugin_name, asset_name)
  
imports: import os
  import queue
  import threading
  from typing import Optional
  from tensorboard.backend.event_processing import directory_watcher
  from tensorboard.backend.event_processing import plugin_event_accumulator
  from tensorboard.backend.event_processing import io_wrapper
  from tensorboard.util import tb_logging
label_desc: Use image node_id 6 for calling the EventMultiplexer obj's underlying member method code with example usage: obj.RetrievePluginAsset(run, plugin_name, asset_name) and returns: accumulator